less operator input, provide greaterimprovements in productivity, andincrease the quality of the machinedpart.
Among several CNC industrialmachining processes, milling is afundamental machining operation. Endmilling is the most common metalremoval operation encountered. It iswidely used in a variety of manufacturing industries including the aerospaceand automotive sectors, where quality is an important factor in the production of slots, pockets, precision molds and dies. The quality of the surface plays a very important role in the performance of milling as a good-quality milled surface significantly improves fatigue strength, corrosion resistance, or creep life. Surface roughness also affects several functional attributes of parts, such as contact causing surface friction, wearing, light reflection, heat transmission, ability of distributing and holding a lubricant, coating, or resisting fatigue. Therefore, the desired finish surface is usually specified and the appropriate processes are selected to reach the required quality.
Several factors will influence the final surface roughness in a CNC milling operation. The final surface roughness might be considered as the sum of two independent effects: 1) the ideal surface roughness is a result of the geometry of tool and feed rate and 2) the natural surface roughness is a result of the irregularities in the cutting operation [Boothroyd & Knight, 1989]. Factors such as spindle speed, feed rate, and depth of cut that control the cutting operation can be setup in advance. However, factors such as tool geometry, tool wear, chip loads and chip formations, or the material properties of both tool and workpiece are uncontrolled (Huynh & Fan, 1992).Even in the occurrence of chatter or vibrations of the machine tool, defects in the structure of the work material,wear of tool, or irregularities of chip formation contribute to the surface damage in practice during machining(Boothroyd & Knight, 1989). One should develop techniques to predict the surface roughness of a product before milling in order to evaluate the fitness of machining parameters such as feed rate or spindle speed for keeping a desired surface roughness and increasing product quality.It is also important that the prediction technique should be accurate, reliable, low-cost, and non-destructive. Therefore, the purpose of this study is to develop one surface prediction technique which is termed the multiple regression prediction model and then evaluate its prediction ability.